Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Create market analysis and forecasts to drive pricing decisions using data analysis and algorithms.
- Company: Join a global consumer business focused on innovation and market leadership.
- Benefits: Enjoy a hybrid work model, excellent remuneration, and a comprehensive benefits package.
- Why this job: Be part of a dynamic team that values collaboration and continuous learning in a fast-paced environment.
- Qualifications: 5+ years in statistical modelling with experience in Python, SQL, and pricing management.
- Other info: This is a full-time, permanent role based in Luton, requiring office presence 2-3 days a week.
The predicted salary is between 36000 - 60000 £ per year.
Job description
Our client, a global consumer business, are currently hiring for a Data Scientist to create market analysis and forecasts to drive pricing decisions. The primary responsibility is to develop, test and operate pricing systems and algorithms using SQL, Python, data analysis and statistics.
Responsibilities
Requirements
This is a full time, permanent position working on a hybrid basis, with the requirement to be in the office in Luton, Beds 2-3 days per week.
Our client offers excellent remuneration and benefits package.
Data Scientist employer: MarkJames Search
Contact Detail:
MarkJames Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science, particularly in pricing strategies and revenue management. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with professionals in the data science field, especially those who have experience in pricing algorithms. Engaging in discussions or attending relevant meetups can provide insights and potentially lead to referrals.
✨Tip Number 3
Brush up on your SQL and Python skills by working on real-world projects or contributing to open-source initiatives. Having practical examples to discuss can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss how you've collaborated with cross-functional teams in the past. Highlighting your ability to liaise with stakeholders will show that you're a team player, which is crucial for this role.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with statistical modelling and programming languages like Python and SQL. Emphasise any relevant projects or roles that demonstrate your ability to develop pricing systems and algorithms.
Craft a Strong Cover Letter: In your cover letter, explain why you are passionate about data science and how your skills align with the responsibilities of the role. Mention specific experiences where you've successfully collaborated with stakeholders or developed innovative solutions.
Showcase Relevant Skills: Clearly list your technical skills, especially those mentioned in the job description such as R, Python, and SQL. If you have experience with C or other relevant software, be sure to include that as well.
Prepare for Potential Questions: Think about how you would answer questions related to your experience in pricing/revenue management and your approach to forecasting and demand modelling. Be ready to discuss specific examples from your past work.
How to prepare for a job interview at MarkJames Search
✨Showcase Your Technical Skills
Make sure to highlight your experience with SQL and Python during the interview. Be prepared to discuss specific projects where you've applied these skills, especially in statistical modelling or pricing algorithms.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would approach market analysis or forecasting challenges, and be ready to explain your thought process.
✨Demonstrate Collaboration Skills
Since the role involves liaising with various stakeholders, be ready to share examples of how you've successfully collaborated with teams in the past. Highlight your communication skills and ability to work in a fast-paced environment.
✨Emphasise Continuous Learning
The client values continuous improvement, so discuss any recent courses, certifications, or self-study you've undertaken to enhance your skills. This shows your commitment to staying updated in the field of data science.
